HMDA Dataset Info¶
<class 'pandas.core.frame.DataFrame'> Index: 3533892 entries, 0 to 4456613 Data columns (total 25 columns): # Column Dtype --- ------ ----- 0 race object 1 sex object 2 co_applicant object 3 age object 4 income float64 5 loan_amount int64 6 property_value_ratio float64 7 mortgage_term object 8 credit_model object 9 debt_to_income_ratio object 10 combined_loan_to_value_ratio float64 11 main_underwriter object 12 tract_to_metro_income_percentage object 13 lender_type object 14 lender_size int64 15 white_population_pct float64 16 metro_name object 17 metro_code object 18 metro_size_percentile object 19 state_code object 20 county_code object 21 census_tract object 22 loan_outcome object 23 lender_id category 24 fips object dtypes: category(1), float64(4), int64(2), object(18) memory usage: 680.9+ MB None
Mortgage outcomes in HMDA data¶
Applicant Characteristics¶
What leads to loan denials?¶
Are disparities focused in any geographic areas?¶
Denial rates in the Chicago metropolitan area:¶
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